v4.14.0 - Faceted and Animated Images and Heatmaps, Inside Tick Labels, Better Axis Type Detection

See the full announcement at https://community.plotly.com/t/announcing-plotly-py-4-14-faceted-and-animated-images-and-heatmaps-inside-tick-labels-better-axis-type-detection/48079

Added

• px.imshow now supports facet_col and animation_frame arguments for visualizing 3-d and 4-d images 2746
• px.defaults now supports color_discrete_map, symbol_map, line_dash_map, labels and category_orders as well as a .reset() method 2957

Fixed

• axes will now auto-type numeric strings as categorical data rather than linear in the default templates 2951

Updated

• Updated Plotly.js to version 1.58.1. See the plotly.js CHANGELOG for more information. These changes are reflected in the auto-generated plotly.graph_objects module. Notable changes include:
  • a new ticklabelposition attribute to enable positioning tick labels inside the plotting area
  • better support for scaleanchor and matches on cartesian axes for matched square subplots
  • a new autotypenumbers attribute which is now set to strict in the default templates
  • various fixes relating to automargins for small figures

v4.13.0 - Magical Error Messages and Documentation, plus Speedups and Faceted Maps

See the fully release announcement at https://community.plotly.com/t/announcing-plotly-py-4-13-magical-error-messages-and-documentation-plus-speedups-and-faceted-maps/47497

Added

• px.choropleth, px.scatter_geo and px.line_geo now support faceting as well as fitbounds and basemap_visible 2923
• px.scatter_geo and px.line_geo now support geojson/featureidkey input 2923
• px.scatter_geo now supports symbol 2923
• go.Figure now has a set_subplots method to set subplots on an already
  existing figure. 2866
• Added Turbo colorscale and fancier swatch display functions
  2882
• A utility function image_array_to_data_uri has been added in
  plotly.utils, in order to transform NumPy arrays to data b64 URIs (which
  can be passed to the source parameter of go.Image, or to layout images).
  2879
• the selector argument to updater/selector functions now accepts ints and strs
  2894

Updated

• the JSON serialization of plotly figures has been accelerated thanks to a
  different handling of Infinity and NaN values. For example, a figure with a
  1000x1000 Heatmap should now serialize 2x faster. 2880
• Coding mistakes with "magic underscores" now return significantly more ergonomic error
  messages 2843
• Error messages related to impossible subplot geometries are now much more helpful
  2897

Fixed

• px.scatter_geo support for text is fixed 2923
• the x and y parameters of px.imshow are now used also in the case where
  an Image trace is used (for RGB data or with binary_string=True). However,
  only numerical values are accepted (while the Heatmap trace allows date or
  string values for x and y). 2761

v4.12.0 - Horizontal and Vertical Lines and Rectangles

See the full release announcement at https://community.plotly.com/t/announcing-plotly-py-4-12-horizontal-and-vertical-lines-and-rectangles/46783

Added

• For add_trace, add_shape, add_annotation and add_layout_image, the row and/or col argument now also accept the string "all". row="all" adds the object to all the subplot rows and col="all" adds the object to all the subplot columns. (#2840)
• Shapes that reference the plot axes in one dimension and the data in another dimension can be added with the new add_hline, add_vline, add_hrect, add_vrect functions, which also support the row="all" and col="all" arguments. (#2840)
• The add_trace, add_shape, add_annotation, add_layout_image, add_hline, add_vline, add_hrect, add_vrect functions accept an argument exclude_empty_subplots which if True, only adds the object to subplots already containing traces or layout objects. This is useful in conjunction with the row="all" and col="all" arguments. (#2840)
• For all go.Figure functions accepting a selector argument (e.g., select_traces), this argument can now also be a function which is passed each relevant graph object (in the case of select_traces, it is passed every trace in the figure). For graph objects where this function returns true, the graph object is included in the selection. (#2844)

Updated

• Updated Plotly.js to version 1.57.1. See the plotly.js CHANGELOG for more information. These changes are reflected in the auto-generated plotly.graph_objects module.

v4.11.0 - Period positioning on date axes

See the full release announcement at https://community.plotly.com/t/announcing-plotly-py-4-12-horizontal-and-vertical-lines-and-rectangles/46783

Updated

• Updated Plotly.js to version 1.56.0. See the plotly.js CHANGELOG for more information. These changes are reflected in the auto-generated plotly.graph_objects module.

v4.10.0 - date-axis improvements, a Faster px.imshow() and Full Figures for Development

See the full announcement at https://community.plotly.com/t/announcing-plotly-py-4-10-date-axis-improvements-a-faster-px-imshow-and-full-figures-for-development/44685

Added

• Added plotly.io.full_figure_for_development() and plotly.graph_objects.Figure.full_figure_for_development() (#2737)

Updated

• Updated Plotly.js to version 1.55.2. See the plotly.js CHANGELOG for more information. These changes are reflected in the auto-generated plotly.graph_objects module.
• px.imshow has a new binary_string boolean argument, which passes the
  image data as a b64 binary string when True. Using binary strings allow for
  faster image rendering and smaller figure size. Additional optional arguments
  binary_backend, binary_format and binary_compression_level control
  how to generate the b64 string (#2691
• px.imshow has a new constrast_rescaling argument in order to choose how
  to set data values corresponding to the bounds of the color range
  (#2691

Fixed

• Plotly Express no longer converts datetime columns of input dataframes to UTC (#2749)
• Plotly Express has more complete support for datetimes as additional hover_data (#2749)
• Histogram selection behaviour with FigureWidget (#2711) with thanks to @meffmadd
• Behaviour of full_html() with html=False (#2469) with thanks to @tallamjr
• ff.distplot() now only computes traces that will be shown (#2730) with thanks to @akbo
• Pandas backend .hist() works with latest version of Pandas (#2713) with thanks to @Kerybas

v4.9.0 - Kaleido for static image export, Hexbin Tile Maps, and Timelines

See the full announcement at https://community.plotly.com/t/announcing-plotly-py-4-9-kaleido-for-static-image-export-hexbin-tile-maps-and-timelines/42524

Added

• Added image export support using Kaleido. The image export backend can be configured using the new engine argument to plotly.io.to_image and plotly.io.write_image. The engine argument may be set to "kaleido", "orca", or "auto". The default is engine="auto", in which case the Kaleido backend is enabled if the kaleido package from PyPI is installed, otherwise Orca is used. (#2613).
• plotly.express.timeline() added as an official alternative to plotly.figure_factories.create_gantt() (#2626)
• create_hexbin_mapbox() added to Figure Factories, with thanks to @RenaudLN for the impressive contribution!
• facet_row_spacing and facet_col_spacing added to Plotly Express cartesian 2d functions (#2614)
• base added to Plotly Express bar and bar_polar functions (#2626)
• px.NO_COLOR constant to override wide-form color assignment in Plotly Express (#2614)

Fixed

• trendline traces are now of type scattergl when render_mode="webgl" in Plotly Express (#2614)
• regression from 4.8.1 whereby "parent" was not accepted as part of path for px.sunburst() and px.treemap() (#2640)
• create_dendrogram() figure factory now works correctly with scipy 1.5.1 (#2627)

Updated

• Updated Plotly.js to version 1.54.6. See the plotly.js CHANGELOG for more information.
• Added all cartesian-2d Plotly Express functions, plus imshow, to Pandas backend with kind option (#2541)
• plotly.express.imshow now uses data frame index and columns names and values to populate axis parameters by default (#2539)
• Javascript extensions are now build using Node 12, and have an updated package-lock.json with many fewer security warnings (#2636)

v4.8.2

See the full announcement at https://community.plotly.com/t/announcing-plotly-py-4-8-plotly-express-support-for-wide-and-mixed-form-data-plus-a-pandas-backend/40048

Updated

• Updated Plotly.js to version 1.54.5. See the plotly.js CHANGELOG for more information. This version includes various bug and security fixes.
• add_traces() now accepts bare int-like values for rows/cols as well as lists thereof (#2546), with thanks to @MCBoarder289 for the contribution!

Fixed

• row/col now accept int-like values, not strictly int values (#2451), with thanks to @MCBoarder289 for the contribution!
• Fixed special cases with px.sunburst and px.treemap with path input (#2524)
• Fixed bug in hover_data argument of px functions, when the column name is changed with labels and hover_data is a dictionary setting up a specific format for the hover data (#2544).
• Made the Plotly Express trendline argument more robust and made it work with datetime x values (#2554)
• Fixed bug in px.sunburst and px.treemap: when the color and values arguments correspond to the same column, a different aggregation function has to be used for the two arguments (#2591)
• Plotly Express wide mode now accepts mixed integer and float columns (#2598)
• Plotly Express range_(x|y) should not impact the unlinked range of marginal subplots (#2600)
• px.line now sets line_group=<variable> in wide mode by default (#2599)
• Corrected some regex warnings (#2577), with thanks to @georgevdd for the contribution!

v4.8.1

See the full announcement at https://community.plotly.com/t/announcing-plotly-py-4-8-plotly-express-support-for-wide-and-mixed-form-data-plus-a-pandas-backend/40048

Fixed

• Fixed the accidental removal of some functions and submodules from plotly.colors and plotly.express.colors

v4.8.0 - Plotly Express Support for Wide- and Mixed-Form Data, plus a Pandas backend

See the full announcement at https://community.plotly.com/t/announcing-plotly-py-4-8-plotly-express-support-for-wide-and-mixed-form-data-plus-a-pandas-backend/40048

Key new documentation pages:

• Wide-form and mixed-form data support in Plotly Express
• Pandas plotting backend

Added

• plotly now provides a Plotly Express-backed Pandas-compatible plotting backend, which can be activated via pandas.options.plotting.backend = "plotly". Note that it is not intended to implement every Pandas plotting function, nor is it intended to replicate the behaviour of every argument, although per the changes below, x and y should behave similarly. (#2336)
• New datasets have been added to plotly.express.data: stocks, experiment, medals_wide and medals_long. (#2336)
• plotly go.Figure and go.FigureWidget now have a _repr_html_ and a _repr_mimebundle_ method, which are standard hooks for integration in systems based on IPython. In particular, with _repr_html_ plotly figures can now be used within sphinx-gallery without any scraper. These additions should not change anything to the way plotly figures are displayed in notebook environments, since the _ipython_display_ method (already present in earlier versions) takes precedence over the new methods.

Updated

• The behaviour of the x, y, orientation, histfunc, violinmode, boxmode and stripmode arguments for 2d-cartesian functions in Plotly Express (i.e. scatter, line, area, bar, histogram, violin, box, strip, funnel, density_heatmap and density_contour) has been refined (#2336):
  • wide-form data support: if either x or y (but not both) may now be provided as a list of column references into data_frame or columns of data, in which case the imputed data frame will be treated as "wide" data and melt()ed internally before applying the usual mapping rules, with function-specific defaults.
  • if neither x nor y is provided but data_frame is, the data frame will be treated as "wide" with defaults depending on the value of orientation (and orientation has accordingly been added to scatter, line, density_heatmap, and density_contour for this purpose). Previously this would have resulted in an empty figure.
  • if x or y is missing, it is inferred to be the index of data_frame if data_frame provided, otherwise a stable index of integers starting at 0. In the case of px.bar, if the provided value is not continuous, the missing value is treated as a column of 1s named "count", so as to behave more like px.histogram and to avoid sizing the resulting bars differently based on their position in the column. Previously, missing values defaulted to integers starting at 0 per trace which made it potentially inconsistent or misleading.
  • if x (y) is missing, orientation now defaults to v (h). Previously it always defaulted to v but this is not considered a breaking change, as the cases in which it now defaults to h caused unreadable output if set to v.
  • if both x and y are provided and one of them does not contain continuous values, orientation defaults to the value perpendicular to that axis. Previously it always defaulted to v but this is not considered a breaking change, as the cases in which it now defaults to h caused unreadable output if set to v.
  • if both x and y are provided to histogram, and if x, y and z are provided to density_heatmap or density_contour, then histfunc now defaults to sum so as to avoid ignoring the provided data, and to cause histogram and bar to behave more similarly.
  • violinmode, boxmode and stripmode now default to overlay if x (y) in in v (h) orientation is also mapped to color, to avoid strange spacing issues with the previous default of group in all cases.
• The Plotly Express arguments color_discrete_map, symbol_map and line_dash_map now accept the string "identity" which causes the corresponding input data to be used as-is rather than mapped into color_discrete_sequence, symbol_sequence or line_dash_sequence, respectively. (#2336)
• Plotly Express now accepts px.Constant or px.Range objects in the place of column references so as to express constant or increasing integer values. (#2336)

v4.7.1

Fixed

• Fix AttributeError: module 'plotly.graph_objs' has no attribute 'FigureWidget' exception on from plotly.graph_objs import * when ipywidgets is not installed. Error also occurred when importing plotly.figure_factor. It is now possible to import plotly.graph_objs.FigureWidget when ipywidgets is not installed, and an informative ImportError exception will be raised in the FigureWidget constructor (#2443, #1111).
• Fix TypeError: unhashable type: 'Template' during Figure construction when plotly.io.templates.default is set to a Template object rather than a string.